Software Engineer - Agent Harness
Listed on 2026-06-19
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Software Development
AI Engineer (Applied/Software), Software Engineer, Backend Developer, DevOps
Mission
At Intel, our journey is to transform AI into something safer, more trustworthy, and respectful of human privacy by design. We believe transformative AI should have a positive impact on people—powerful in capability, yet honest about its limits and protective of the data and resources it touches. To get there, we build agentic AI that combines the best of local and cloud intelligence—private, affordable, and sustainable by design.
Small, efficient models run directly on the user's machine, keeping data private and token costs low, while powerful cloud models handle the hardest work: planning, reasoning, and complex problem-solving. We build intelligence that scales without sacrificing trust, cost, or the planet—because the future of AI should belong to the people it serves.
The model is only half an agent; the harness is the other half. You build everything around the model that makes it act—including context management, tool and function calling, file and terminal execution, scheduling, memory, and the agent loop itself. This is core product engineering on an agent framework comparable to well‑known AI models, but built to run hybrid (local + cloud) and with efficiency.
Responsibilities- Design and build the agent loop: planning, tool invocation, observation handling, retries, termination.
- Implement tool integrations—including file I/O, terminal/shell execution, web, MCP servers, message apps.
- Build context management: what goes in the window, when to summarize, how to use long/cross‑session memory.
- Implement scheduling and automatic/background task execution.
- Keep the harness model‑agnostic so local and cloud models are swappable behind one abstraction.
- Design agent security mechanisms through different approaches.
- Make the loop observable, debuggable: tracing, replay, and reproducible agent sessions.
- Partner with the SRE/Production squad for shipping and running it reliably in production; you do not carry the pager.
Curiosity is required. You will develop: how frontier agent harnesses are architected—and how to do it efficiently; hybrid model routing and graceful degradation; the hard parts: context‑window economics, tool‑call reliability, and multi‑agent orchestration. Interest in LLM agents and how they actually work under the hood.
Qualifications- BS/MS in CS, EE, Math or related STEM field.
- 5+ years software development background.
- Strong in at least one of Python, Type Script, Go, Rust, C++.
- Comfortable with async, concurrency, and process/subprocess management.
- Has built a project that calls external tools or APIs in a loop and handled the failure modes.
- Experienced at reading unfamiliar codebases and someone else’s runtime.
- Experience with agent frameworks, tool/function calling, or MCP.
- Built developer tooling, CLIs, or IDE‑adjacent products.
- Familiarity with sandboxing, containerization, and safe code execution.
- Contributions to open‑source agent/LLM tooling.
- Experience with agent security.
Intel offers a competitive compensation package that includes pay, stock bonuses, and benefit programs such as health, retirement, and vacation.
Work ModelThis role will be eligible for a hybrid work model, which allows employees to split their time between working on‑site at their assigned Intel site and off‑site.
Job DetailsJob Type: Shift 1 (United States of America). Primary
Location:
US, California, Santa Clara with additional locations in Arizona (Phoenix), California (Folsom), Oregon (Hillsboro). Business group:
The Client Computing Group (CCG).
All qualified applicants will receive consideration for employment without regard to race, color, religion, religious creed, sex, national origin, ancestry, age, physical or mental disability, medical condition, genetic information, military and veteran status, marital status, pregnancy, gender, gender expression, gender identity, sexual orientation, or any other characteristic protected by local law, regulation, or ordinance.
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